{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cfa76efb",
   "metadata": {},
   "source": [
    "# Oscilloscope\n",
    "\n",
    "With the PSLab's oscilloscope, we can capture a time series of voltage values on up to three channels simultaneously. In this tutorial, we will learn how to use pslab-python to control the oscilloscope.\n",
    "\n",
    "Start by importing the library and connecting to the device:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "63506073",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pslab\n",
    "psl = pslab.ScienceLab()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16f28b92",
   "metadata": {},
   "source": [
    "The `ScienceLab` class provides a common interface to the PSLab's instruments, the oscilloscope being one example. Let's take a look at how we can use it to collect some data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "0d775bb1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x: [ 0. 10. 20. 30. 40.]\n",
      "y: [0.07655678 0.07655678 0.07655678 0.06849817 0.09267399]\n"
     ]
    }
   ],
   "source": [
    "x, y = psl.oscilloscope.capture(channels=1, samples=5, timegap=10)\n",
    "print(\"x:\", x)\n",
    "print(\"y:\", y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae595153",
   "metadata": {},
   "source": [
    "Here, we tell the oscilloscope to read five voltage samples from one channel (specifically, the CH1 pin), with each sample being read ten microseconds after the previous one. The `Oscilloscope.capture` method returns a pair of arrays. The first array contains timestamps in microseconds for when every sample was collected, while the second array contains the actual samples.\n",
    "\n",
    "Note that the first x value is zero. This marks the starting point for data collection, and every subsequent x value is the number of µs that have passed since reading began.\n",
    "\n",
    "The y values are all close to zero, which is unsurprising since nothing is connected to CH1. They're not *exactly* zero, which is due to a number of factors such as electromagnetic noise in the environment, electromagnetic noise from the PSLab itself, and from imperfections in the ADC.\n",
    "\n",
    "Looking at the data in this manner is fine for very short time series, but quickly becomes unwieldy when we increase the number of samples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "29e79fa2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x: [   0.   10.   20.   30.   40.   50.   60.   70.   80.   90.  100.  110.\n",
      "  120.  130.  140.  150.  160.  170.  180.  190.  200.  210.  220.  230.\n",
      "  240.  250.  260.  270.  280.  290.  300.  310.  320.  330.  340.  350.\n",
      "  360.  370.  380.  390.  400.  410.  420.  430.  440.  450.  460.  470.\n",
      "  480.  490.  500.  510.  520.  530.  540.  550.  560.  570.  580.  590.\n",
      "  600.  610.  620.  630.  640.  650.  660.  670.  680.  690.  700.  710.\n",
      "  720.  730.  740.  750.  760.  770.  780.  790.  800.  810.  820.  830.\n",
      "  840.  850.  860.  870.  880.  890.  900.  910.  920.  930.  940.  950.\n",
      "  960.  970.  980.  990. 1000. 1010. 1020. 1030. 1040. 1050. 1060. 1070.\n",
      " 1080. 1090. 1100. 1110. 1120. 1130. 1140. 1150. 1160. 1170. 1180. 1190.\n",
      " 1200. 1210. 1220. 1230. 1240. 1250. 1260. 1270. 1280. 1290. 1300. 1310.\n",
      " 1320. 1330. 1340. 1350. 1360. 1370. 1380. 1390. 1400. 1410. 1420. 1430.\n",
      " 1440. 1450. 1460. 1470. 1480. 1490. 1500. 1510. 1520. 1530. 1540. 1550.\n",
      " 1560. 1570. 1580. 1590. 1600. 1610. 1620. 1630. 1640. 1650. 1660. 1670.\n",
      " 1680. 1690. 1700. 1710. 1720. 1730. 1740. 1750. 1760. 1770. 1780. 1790.\n",
      " 1800. 1810. 1820. 1830. 1840. 1850. 1860. 1870. 1880. 1890. 1900. 1910.\n",
      " 1920. 1930. 1940. 1950. 1960. 1970. 1980. 1990. 2000. 2010. 2020. 2030.\n",
      " 2040. 2050. 2060. 2070. 2080. 2090. 2100. 2110. 2120. 2130. 2140. 2150.\n",
      " 2160. 2170. 2180. 2190. 2200. 2210. 2220. 2230. 2240. 2250. 2260. 2270.\n",
      " 2280. 2290. 2300. 2310. 2320. 2330. 2340. 2350. 2360. 2370. 2380. 2390.\n",
      " 2400. 2410. 2420. 2430. 2440. 2450. 2460. 2470. 2480. 2490. 2500. 2510.\n",
      " 2520. 2530. 2540. 2550. 2560. 2570. 2580. 2590. 2600. 2610. 2620. 2630.\n",
      " 2640. 2650. 2660. 2670. 2680. 2690. 2700. 2710. 2720. 2730. 2740. 2750.\n",
      " 2760. 2770. 2780. 2790. 2800. 2810. 2820. 2830. 2840. 2850. 2860. 2870.\n",
      " 2880. 2890. 2900. 2910. 2920. 2930. 2940. 2950. 2960. 2970. 2980. 2990.\n",
      " 3000. 3010. 3020. 3030. 3040. 3050. 3060. 3070. 3080. 3090. 3100. 3110.\n",
      " 3120. 3130. 3140. 3150. 3160. 3170. 3180. 3190. 3200. 3210. 3220. 3230.\n",
      " 3240. 3250. 3260. 3270. 3280. 3290. 3300. 3310. 3320. 3330. 3340. 3350.\n",
      " 3360. 3370. 3380. 3390. 3400. 3410. 3420. 3430. 3440. 3450. 3460. 3470.\n",
      " 3480. 3490. 3500. 3510. 3520. 3530. 3540. 3550. 3560. 3570. 3580. 3590.\n",
      " 3600. 3610. 3620. 3630. 3640. 3650. 3660. 3670. 3680. 3690. 3700. 3710.\n",
      " 3720. 3730. 3740. 3750. 3760. 3770. 3780. 3790. 3800. 3810. 3820. 3830.\n",
      " 3840. 3850. 3860. 3870. 3880. 3890. 3900. 3910. 3920. 3930. 3940. 3950.\n",
      " 3960. 3970. 3980. 3990. 4000. 4010. 4020. 4030. 4040. 4050. 4060. 4070.\n",
      " 4080. 4090. 4100. 4110. 4120. 4130. 4140. 4150. 4160. 4170. 4180. 4190.\n",
      " 4200. 4210. 4220. 4230. 4240. 4250. 4260. 4270. 4280. 4290. 4300. 4310.\n",
      " 4320. 4330. 4340. 4350. 4360. 4370. 4380. 4390. 4400. 4410. 4420. 4430.\n",
      " 4440. 4450. 4460. 4470. 4480. 4490. 4500. 4510. 4520. 4530. 4540. 4550.\n",
      " 4560. 4570. 4580. 4590. 4600. 4610. 4620. 4630. 4640. 4650. 4660. 4670.\n",
      " 4680. 4690. 4700. 4710. 4720. 4730. 4740. 4750. 4760. 4770. 4780. 4790.\n",
      " 4800. 4810. 4820. 4830. 4840. 4850. 4860. 4870. 4880. 4890. 4900. 4910.\n",
      " 4920. 4930. 4940. 4950. 4960. 4970. 4980. 4990.]\n",
      "y: [ 0.06849817  0.07655678 -0.0040293   0.07655678  0.05238095  0.06849817\n",
      "  0.06043956  0.06043956  0.07655678  0.05238095  0.07655678  0.06043956\n",
      "  0.07655678  0.06849817  0.07655678  0.06849817  0.06849817  0.07655678\n",
      "  0.06043956  0.08461538  0.06043956  0.08461538  0.06849817  0.08461538\n",
      "  0.07655678  0.07655678  0.08461538  0.06849817  0.08461538  0.06043956\n",
      "  0.08461538  0.06849817  0.08461538  0.07655678  0.07655678  0.08461538\n",
      "  0.06849817  0.08461538  0.06043956  0.08461538  0.06043956  0.07655678\n",
      "  0.06849817  0.06043956  0.07655678  0.06043956  0.08461538  0.05238095\n",
      "  0.07655678  0.05238095  0.06849817  0.06043956  0.06043956  0.07655678\n",
      "  0.06043956  0.07655678  0.05238095  0.07655678  0.06043956  0.06849817\n",
      "  0.06849817  0.06043956  0.07655678  0.06043956  0.07655678  0.06043956\n",
      "  0.07655678  0.06043956  0.07655678  0.06849817  0.07655678  0.07655678\n",
      "  0.06849817  0.09267399  0.06043956  0.08461538  0.06849817  0.08461538\n",
      "  0.07655678  0.07655678  0.08461538  0.06849817  0.09267399  0.06849817\n",
      "  0.09267399  0.06043956  0.08461538  0.06849817  0.07655678  0.07655678\n",
      "  0.06849817  0.08461538  0.06043956  0.08461538  0.06043956  0.08461538\n",
      "  0.06849817  0.06849817  0.06849817  0.06043956  0.07655678  0.06043956\n",
      "  0.07655678  0.06043956  0.06849817  0.06043956  0.06043956  0.06849817\n",
      "  0.06043956  0.07655678  0.05238095  0.07655678 -0.0040293   0.07655678\n",
      "  0.06043956  0.06849817  0.06849817  0.06043956  0.07655678  0.05238095\n",
      "  0.08461538  0.06043956  0.08461538  0.06849817  0.06849817  0.07655678\n",
      "  0.06849817  0.08461538  0.06043956  0.08461538  0.06043956  0.08461538\n",
      "  0.06849817  0.07655678  0.07655678  0.06849817  0.08461538  0.06043956\n",
      "  0.08461538  0.06849817  0.08461538  0.06849817  0.07655678  0.07655678\n",
      "  0.06849817  0.08461538  0.06043956  0.08461538  0.06043956  0.08461538\n",
      "  0.06849817  0.07655678  0.06849817  0.06849817  0.07655678  0.06043956\n",
      "  0.08461538  0.05238095  0.07655678  0.06043956  0.06849817  0.06849817\n",
      "  0.05238095  0.07655678  0.06043956  0.07655678  0.05238095  0.07655678\n",
      "  0.06043956  0.06043956  0.06849817  0.06043956  0.06849817  0.06043956\n",
      "  0.07655678  0.06043956  0.07655678  0.06043956  0.07655678  0.06849817\n",
      "  0.07655678  0.07655678  0.06043956  0.08461538  0.06043956  0.08461538\n",
      "  0.06849817  0.07655678  0.07655678  0.06849817  0.08461538  0.06043956\n",
      "  0.08461538  0.06043956  0.08461538  0.07655678  0.08461538  0.07655678\n",
      "  0.06849817  0.08461538  0.06849817  0.08461538  0.06043956  0.08461538\n",
      "  0.06849817  0.07655678  0.07655678  0.06849817  0.08461538  0.06043956\n",
      "  0.08461538  0.06043956  0.08461538  0.06043956  0.06849817  0.06849817\n",
      "  0.06043956  0.07655678  0.05238095  0.07655678  0.05238095  0.07655678\n",
      "  0.06043956  0.06849817  0.06043956  0.06849817  0.06849817  0.06043956\n",
      "  0.07655678  0.06043956  0.07655678  0.06043956  0.07655678  0.06849817\n",
      "  0.06849817  0.07655678  0.06849817  0.08461538  0.06043956  0.08461538\n",
      "  0.06043956  0.09267399  0.06849817  0.07655678  0.07655678  0.06849817\n",
      "  0.08461538  0.06849817  0.08461538  0.06043956  0.09267399  0.06849817\n",
      "  0.08461538  0.07655678  0.07655678  0.08461538  0.06849817  0.08461538\n",
      "  0.06849817  0.08461538  0.06043956  0.08461538  0.06849817  0.07655678\n",
      "  0.07655678  0.06043956  0.07655678  0.06043956  0.07655678  0.05238095\n",
      "  0.07655678 -0.0040293   0.07655678  0.06043956  0.06043956  0.06849817\n",
      "  0.06043956  0.07655678  0.05238095  0.07655678  0.06043956  0.07655678\n",
      "  0.06849817  0.06849817  0.07655678  0.06849817  0.07655678  0.06043956\n",
      "  0.08461538  0.06043956  0.08461538  0.06849817  0.07655678  0.07655678\n",
      "  0.07655678  0.08461538  0.06849817  0.09267399  0.06849817  0.09267399\n",
      "  0.06849817  0.08461538  0.06849817  0.07655678  0.07655678  0.06849817\n",
      "  0.08461538  0.06043956  0.09267399  0.06043956  0.08461538  0.06043956\n",
      "  0.07655678  0.06849817  0.06043956  0.07655678  0.06043956  0.07655678\n",
      "  0.06043956  0.07655678  0.06043956  0.06849817  0.06043956  0.06043956\n",
      "  0.07655678  0.05238095  0.07655678  0.05238095  0.07655678  0.06043956\n",
      "  0.06849817  0.06849817  0.06043956  0.07655678  0.05238095  0.08461538\n",
      "  0.06043956  0.07655678  0.06849817  0.07655678  0.06849817  0.06849817\n",
      "  0.08461538  0.06043956  0.08461538  0.06043956  0.08461538  0.06849817\n",
      "  0.07655678  0.07655678  0.06849817  0.08461538  0.06043956  0.08461538\n",
      "  0.06849817  0.08461538  0.07655678  0.07655678  0.08461538  0.06849817\n",
      "  0.08461538  0.06043956  0.08461538  0.06849817  0.07655678  0.07655678\n",
      "  0.06043956  0.08461538  0.06043956  0.08461538  0.06043956  0.07655678\n",
      "  0.06043956  0.06043956  0.07655678  0.06043956  0.07655678  0.06043956\n",
      "  0.07655678  0.05238095  0.06849817  0.06043956  0.06043956  0.06849817\n",
      "  0.06043956  0.07655678  0.06043956  0.07655678  0.06043956  0.06849817\n",
      "  0.06849817  0.06043956  0.08461538  0.06043956  0.08461538  0.06043956\n",
      "  0.07655678  0.06849817  0.06849817  0.07655678  0.06849817  0.08461538\n",
      "  0.06849817  0.08461538  0.06849817  0.08461538  0.07655678  0.07655678\n",
      "  0.08461538  0.06849817  0.08461538  0.06849817  0.08461538  0.06849817\n",
      "  0.07655678  0.08461538  0.06043956  0.08461538  0.06043956  0.07655678\n",
      "  0.06043956  0.07655678  0.06849817  0.06849817  0.07655678  0.06043956\n",
      "  0.07655678  0.06043956  0.08461538  0.05238095  0.06849817  0.06849817\n",
      "  0.06043956  0.07655678  0.05238095  0.07655678  0.05238095  0.06849817\n",
      "  0.06043956  0.06043956  0.07655678  0.06043956  0.08461538  0.06043956\n",
      "  0.07655678  0.06043956  0.07655678  0.06849817  0.06849817  0.07655678\n",
      "  0.06043956  0.08461538  0.06043956  0.08461538  0.06849817  0.06849817\n",
      "  0.08461538  0.06849817  0.09267399  0.06849817  0.08461538  0.06849817\n",
      "  0.07655678  0.08461538  0.06849817  0.08461538  0.06849817  0.07655678\n",
      "  0.06849817  0.07655678  0.06849817  0.06849817  0.07655678  0.06849817\n",
      "  0.06849817  0.06849817  0.06849817  0.06849817  0.06043956  0.06849817\n",
      "  0.06043956  0.06849817  0.06043956  0.06043956  0.06043956  0.06043956\n",
      "  0.06849817  0.06043956  0.06849817  0.06043956  0.06849817  0.06849817\n",
      "  0.06849817  0.06849817  0.06849817  0.06849817  0.06849817  0.06849817\n",
      "  0.06849817  0.07655678]\n"
     ]
    }
   ],
   "source": [
    "x, y = psl.oscilloscope.capture(channels=1, samples=500, timegap=10)\n",
    "print(\"x:\", x)\n",
    "print(\"y:\", y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8686289c",
   "metadata": {},
   "source": [
    "Not exactly easy to read. Of course, we are using an oscilloscope, so it makes more sense to plot the data. The `matplotlib` library provides a convenient way to accomplish this.:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "4dd57bcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fd794d0ea70>]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "x, y = psl.oscilloscope.capture(channels=1, samples=500, timegap=10)\n",
    "plt.plot(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6104783",
   "metadata": {},
   "source": [
    "Let's use the programmable power supply from the previous chapter to generate a more interesting signal:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9ebd5a01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fd7954b1fc0>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import time\n",
    "x = np.arange(0, 2 * np.pi, np.pi / 100)\n",
    "y = np.sin(x)\n",
    "(x,) = psl.oscilloscope.capture(1, 10000, 100, block=False)\n",
    "for v in y:\n",
    "    psl.power_supply.pv1 = v\n",
    "(y,) = psl.oscilloscope.fetch_data()\n",
    "plt.plot(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "280d42fe",
   "metadata": {},
   "source": [
    "Next, we're going to sample data from two channels at once, and plot the result:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "7d574298",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f0101512620>,\n",
       " <matplotlib.lines.Line2D at 0x7f0101512680>]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x, y, z = psl.oscilloscope.capture(channels=2, samples=500, timegap=10)\n",
    "plt.plot(x, y, x, z)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d754abb",
   "metadata": {},
   "source": [
    "Note that we need to assign one additional variable, z. This is because `Oscilloscope.capture` returns one additional array for every sampled channel. The y variable holds the samples from CH1, as before, and z holds the samples from CH2.\n",
    "\n",
    "Collecting samples from three channels follows the sampe principle; just add an additional capture variable to hold the samples from CH3.\n",
    "\n",
    "That's the basic features of the PSLab's oscilloscope. It has more features that we haven't covered yet, including triggering and sample range selection, but before we look at those we need to introduce a few other instruments."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
